Clustering fibromyalgia patients: A combination of psychosocial and somatic factors leads to resilient coping in a subgroup of fibromyalgia patients

Abstract

Background: Coping strategies and their efficacy vary greatly in patients suffering from fibromyalgia syndrome (FMS).

Objective: We aimed to identify somatic and psychosocial factors that might contribute to different coping strategies and resilience levels in FMS.

Subjects and methods: Standardized questionnaires were used to assess coping, pain, and psychological variables in a cohort of 156 FMS patients. Quantitative real-time polymerase chain reaction (qRT-PCR) determined gene expression of selected cytokines in white blood cells of 136 FMS patients and 25 healthy controls. Data of skin innervation, functional and structural sensory profiles of peripheral nociceptive nerve fibers of a previous study were included into the statistics. An exploratory factor analysis was used to define variance explaining factors, which were then included into cluster analysis.

Results: 54.9% of the variance was explained by four factors which we termed (1) affective load, (2) coping, (3) pain, and (4) pro-inflammatory cytokines (p < 0.05). Considering differences in the emerged factors, coping strategies, cytokine profiles, and disability levels, 118 FMS patients could be categorized into four clusters which we named "maladaptive", "adaptive", "vulnerable", and "resilient" (p < 0.05). The adaptive cluster had low scores in disability and in all symptom categories in contrast to the vulnerable cluster, which was characterized by high scores in catastrophizing and disability (p < 0.05). The resilient vs. the maladaptive cluster was characterized by better coping and a less pro-inflammatory cytokine pattern (p < 0.05).

Conclusion: Our data suggest that problem- and emotion-focused coping strategies and an anti-inflammatory cytokine pattern are associated with reduced disability and might promote resilience. Additional personal factors such as low anxiety scores, ability of acceptance, and persistence further favor a resilient phenotype. Individualized therapy should take these factors into account.

Fig 1. Relative gene expression of selected anti- and pro-inflammatory cytokines in FMS patients and healthy controls.

Boxplots show deltaCT values, i.e. relation of the CT value of the target normalized to the housekeeping gene 18sRNA, of IL-10 (A), IL-4 (B), IL-6 (C) and TNF (D) of patients with FMS and healthy controls. Data are presented as 1/ΔCT. No intergroup difference was found for any of the investigated targets. Note the high variability within the patient group. Abbreviations: CT = cycle threshold; FMS = Fibromyalgia syndrome; IL = Interleukine; TNF = Tumor necrosis factor-alpha.

Fig 2. Four clusters differentiated by four factors explaining the variance in somatic and psychosocial data within the patient group.

Bars symbolize positive or negative difference of this cluster in one specific factor to the mean value in this factor of the entire group. No bar symbolizes no difference of the group in this factor to the mean value of the factor of the entire group. Cluster A (named “maladaptive”) consists of 35 patients, Cluster B the “adaptive” cluster of 40, Cluster C the “vulnerable” cluster of 22 FMS patients and cluster D (named “resilient”) of 21 patients. Significant differences between factors and groups are marked (p < 0.05). Abbreviations: FMS = Fibromyalgia Syndrome.

Fig 3. Differences of the clusters in FMS impact in life (A) and self-reported quality of life (B).

Boxplots of all clusters show differences in all plotted sum score variables resulting in different severity level of the clusters. Significant differences are marked (p < 0.05). Abbreviations: FIQ = Fibromyalgia Impact Questionnaire; FMS = Fibromyalgia Syndrome; SF-12 = 12-items Short-Form Health Survey; PCS = Physical Component Summary; MCS = Mental Component Summary.

Fig 4. Differences between clusters regarding coping strategies.

Bars illustrate the different proportion of the clusters A to D on the mean value of 8 subscale scores of the CSQ-D questionnaire indicating different coping strategies and 2 scores indicating efficiency of these strategies. The coping pattern of the vulnerable cluster is characterized by the high impact of catastrophizing (p < 0.05), the coping of the maladaptive cluster shows higher values in less effective passive strategies with relatively high values in catastrophizing, the adaptive clusters copes with effective problem and emotion-focused strategies with high values in pain control and reduction (p < 0.05) and the resilient cluster uses cognitive based coping strategies with high efficiency in pain control. Abbreviations: CSQ = Coping Strategies Questionnaire.

Fig 5. Cluster specific cytokine profiles.

Bars illustrate mean deltaCT values of the target normalized to the housekeeping gene 18sRNA, of IL-4, IL-6, IL-10 and TNF of patients with FMS organized by the four defined clusters. Results are presented as 1/ΔCT. Relative gene expression of IL-10 between cluster A and D, and between cluster C and D are marked as significant (p < 0.05). Abbreviations: FMS = Fibromyalgia Syndrome; IL = Interleukine; TNF = Tumor necrosis factor-alpha.

Fig 6. Cluster-specific case description and treatment options.

Four profiles of FMS patients per cluster were selected, and possible interventions are listed based on cluster characteristics and missing resources of the vulnerable and maladaptive cluster to improve the severe and maladaptive phenotypes. Abbreviations: MBCT = Mindfulness-Based Cognitive Therapy. MBSR: Mindfulness-Based Stress Reduction.